Interleaved Block-Sparse Transform

IF 3.7 3区计算机科学 Q2 TELECOMMUNICATIONS

IEEE Communications Letters Pub Date : 2025-02-14 DOI:10.1109/LCOMM.2025.3542388

Lei Liu;Ming Wang;Shufeng Li;Yuhao Chi;Ning Wei;Zhaoyang Zhang

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引用次数: 0

Abstract

Low-complexity Bayes-optimal memory approximate message passing (MAMP) is an efficient signal estimation algorithm. However, achieving replica Bayes optimality with MAMP necessitates a large-scale right-unitarily invariant transformation, which is prohibitive in practical systems due to its high computational complexity and hardware costs. To solve this problem, this letter proposes a low-complexity interleaved block-sparse (IBS) transform and a corresponding IBS cross-domain memory approximate message passing (IBS-CD-MAMP) estimator applicable to multiple scenarios, which consist of multiple low-dimensional transform matrices interleaved in an innovative manner and leverage various fast algorithms, to reduce the hardware requirements while mitigating performance loss. Numerical results show that our approach reduces the hardware implementation scale to under 10% and complexity by over 50% with excellent performance in the considered large-scale compressed sensing and multicarrier communication scenarios. This offers efficient solutions for resource-constrained scenarios, which are limited by practical hardware scale and complexity constraints in large-scale communication systems.

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交错块解析变换

低复杂度贝叶斯-最优记忆近似消息传递（MAMP）是一种高效的信号估计算法。然而，使用MAMP实现复制贝叶斯最优性需要大规模的右酉不变变换，由于其高计算复杂性和硬件成本，这在实际系统中是禁止的。为了解决这一问题，本文提出了一种适用于多种场景的低复杂度交错块稀疏（IBS）变换和相应的IBS跨域内存近似消息传递（IBS- cd - mamp）估计器，该估计器以创新的方式由多个低维变换矩阵交错组成，并利用各种快速算法，以降低硬件要求，同时减轻性能损失。数值结果表明，该方法在考虑大规模压缩感知和多载波通信场景时，将硬件实现规模降低到10%以下，将复杂度降低50%以上，并具有优异的性能。这为大规模通信系统中受实际硬件规模和复杂性限制的资源受限场景提供了有效的解决方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Communications Letters 工程技术-电信学

CiteScore

8.10

自引率

7.30%

发文量

590

审稿时长

2.8 months

期刊介绍： The IEEE Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of communication over different media and channels including wire, underground, waveguide, optical fiber, and storage channels. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of communication systems.